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8 Success Factors to Use Business Intelligence

business intelligence, business intelligence systems, intelligence systems, business

Source: Cloud Data Integration Software | Matillion

Introduction  

Business intelligence can be completely transformational if done correctly.  Users can get access to self-service reports which in turn creates a faster and more efficient timetable.  Well-designed data warehouses can reduce errors and possible conflicts in the information found.  All that needs to be done to make sure that this happens is to build a good business intelligence system.   

4 Factors of Successful Business Intelligence   

  1. Don’t Focus on Every Type of Data – Focus on one subject.  Which area would benefit the most from getting better reports?  Work on that area until fully improved, then move onto the next area.  It’ll help to build your reputation among the competition.  It seems like will help to lower your costs and shorten timelines also because of the more streamlined setup. 
  2. Ease of Use – The front end needs to be with no complicated, less understood technical terms.  Along with this creating ease of use, tables help make finding data easier.  And then reports can be built this way if not using self-service options.  In other words, have a search option available so that people can find data through a browser instead of through programming alone.    
  3. High Performance – Try using modern technology when building your business intelligence system.  in-memory analytics, columnar databases, SSD disks and advanced caching will help to speed up your system, therefore making all users happier to do the work. 
  4. Choose Technology Carefully – Don’t just go for the one that’s bundled to what you have already.  Make sure you check out everything and all your options first before deciding to go for the easiest.  Consequently, you might get more bang for your buck and save at the same time. 

4 More Factors to Consider

  1. Understand the Cost – When you see the license it’s really only about 20% of the cost itself.  The other 80% includes hardware, consultancy, and software to run the databases and operating systems in some cases.  It’s not always this way, but it’s something to consider when shopping around. 
  2. Advocates – Who are your domain experts?  They can become your advocates as they really have a full understanding of what your reporting requirements are. They can test the numbers and turn in the reports correctly.  Because of this, they are your best bet for getting the rest of the workers to accept implementing the new system more quickly in the work area. 
  3. Reconcile – You have to make sure that your numbers add up correctly, or you’ll have your users losing faith in you and your company.  Ensure the reconciling of the numbers back to trusted sources in order to make sure everything adds up correctly.  If including calculations allow a way for the user to find out what they mean through something like tool-tips.   
  4. Involving the Executives – Business intelligence works much better with involving executives then not.  Because of this, the executives can make decisions easier and more quickly, along with allocating resources to the right places. 

Summary 

Involving everyone in the process of implementing a new business intelligence system is a priority.  It’s like anywhere else.  It the worker doesn’t see interest in the executives and managers, then they aren’t going to want to work with it either.  Consequently, it could cause you problems in the future and a loss of money.  To deter this from happening, make sure all are on board to support implementing the new system.  Focus on small areas first to improve, then move to other areas.  This will help you to not spread yourself too thin.  Make sure that the system is put into action is easy for everyone to use and is high performance.  Otherwise, people will really hate to work with because it’s too slow.  It won’t be cheap to build either, so make sure you shop around for what you really need instead of what’s there.  If you do this, your business intelligence system could become one of the best.   

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4 Best Practices for Big Data Privacy

big data, data, data privacy, privacy, security, data security, cloud, cloud storage

Source: TechTarget

Introduction 

Big data is becoming a more popular method of gathering data for business purposes.  It seems like it isn’t just for storing data anymore.  As a result, more companies are using the data to gather useful information via business events.  This can be anything from reviewing contracts to finding new ways to entice potential customers to your store.  Because of this it doesn’t have the old way of doing things like passing information from the company server to data storage.  Consequently, it uses virtualization architecture to draw from large content stores and archives; as a result of finding this information, it becomes a global resource.  In turn this allows for better forecasting and predictions that might actually work. 

Sources of Privacy Concerns 

  • Quality and Accuracy of Data – How will it possibly negatively affect people in decisions being made?  How does the Internet affect data through possible bad Internet searches?  Is it possible that the scientist looking up the information might be using unverified information without realizing it? 

Best Practices in Big Data Privacy 

  1. Developing High Competency – You need to become extremely proficient in finding, buying and managing cloud services which are considered an intragyral part of big data for keeping costs down.    There are also companies that prefer not to make the investment and in its place use cloud-based applications, infrastructure, and processing power.  Anyways around it, to ensure privacy there has to be constant monitoring and audits of cloud services that your company is using.  Checking on data integrity, confidentiality and availability are all a must. 
  2. Implementing Converged Storage – It’s much more efficient and reduces possible errors.  Because of this, it increases data quality and accuracy.  There’s going to be a reducing of duplicate data being stored in the same locations and increase cost efficiency too. 
  3. Properly Sanitizing Data –  Make sure to analyze, filter, join, diagnose data at the earliest possible touch points.  It’ll make work much easier without having to go back fixing errors while saving you money in the long run. 
  4. Encourage and Invite – Make some sort of process for consumers to be able to gain access to, review and correct information already collected on them, being at no cost and user-friendly.  Ensure finding privacy policies are easy to reach.  Most of all, make sure to have an easy way for people to contact you with questions or concerns that they have.   Transparency and ease of access to be able to talk to you is key. 

Summary 

Asking for the consent of gathering information is not enough now.   In conclusion, there’s so much gathering of data from others that it isn’t really a question to ask.  More on point is something like telling customers how they can restrict the use of their information or delete it.  Consequently, it’s not something that all companies would offer to their customers, therefore you should try it.  This is something that most likely is going to become a requirement for companies to tell customers in the future.  It seems that enabling privacy using best practices is going to be your best bet.  Most noteworthy it will help to increase the levels of trust and transparency that you and your customers will have in the long run, while saving money at the same time. 

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Top 3 Cybersecurity Trends (via iamwire)

cybersecurity, security, cloud, iot, internetofthings, hackers, allowing hackers

Source: iamwire

Introduction  

Keeping up with cybersecurity measures to keep your computer and system safe is becoming more and more difficult.  Hackers are coming up with new and unusual ways to break into systems all the time.  Sometimes it’s for work, sometimes it’s for fun and sometimes it’s for criminal purposes.  The thing is, if you want to have a reputation for being a safe online store where people can visit and shop without fearing that their data will be taken, then you always have to be on top of what’s going on in the cybersecurity world. 

Just some statistics from 2016 to help show how important cybersecurity is today.  It’s a little outdated, but it gets the point across.   

  • 18 million new malware samples were taken in the 3rd quarter alone. 
  • In the year 2016, there were 400 ransomeware attacks every day. 
  • 78% of people still click on unknown links even though they know about the danger of doing this.  

3 Cybersecurity Trends  

  1. More IoT for Business Operations – The Internet of Things is becoming more popular every day in working environments.  Because of this, it’s making corporate networks vulnerable as there are so many windows where attacks can come through now.  These devices being used for IoT are not secure, allowing hackers to make programs and fake apps that people might download to make work easier, not knowing that they are allowing hackers entry into the system.  Vigilance is key to predict and find where an attack is happening. 
  2. Mobile Threats are Rising Smartphones are the PDA of the ’90’s.  Hackers can use these phones and are using them to spy, use extortion and steal data from companies.  As the smartphone becomes more popular as a tool when offsite, working from home, or in the company, it allows for many more types of opportunities for criminal hackers to gain entry. 
  3. Security of the Cloud –  As the cloud is becoming popular as a place to store all sorts of data, make sure to check the security being used by the company you’re working with.  If their security isn’t up to date, it doesn’t make sense to use them as your data will be vulnerable to attacks.  Make sure to look up their security policies and see when they conduct updates so you get a better idea of how well they take security seriously.  If it isn’t to your standards, then keep shopping.  There are lots of third-party vendors out there dealing with cloud environments.  Also make sure to manage the cloud program after implementing it, along with login credentials.  If either is being poorly taken care of, hackers will find a way in.  

Summary 

Invest in an upgrade, making your company safer for your employees and shoppers to work and shop there.   They will appreciate it and so will you in the long run.  Better to spend the money this way instead of having to hire someone to come and fix your system after being infected by an attack. 

 

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Top 10 Strategic Tech Trends for 2018 (via gartner)

tech, trends, AI, ai, internet of things, iot, cybersecurity, security, machine learning, deep learning

Source: www.gartner.com

Introduction  

With all the trends coming out for this year alone, I decided to look at strategic information systems planning (SISP) trends for a change.  It’s very interesting to see how they actually plan on possibly implementing these new trends that are coming out all the time.  Here’s the list… 

 10 Trends for Strategic IS Planning

AI and Machine Learning Immersion

  1. AI Foundations – This is considered to be the next big battlefield between vendors who build these systems until at least 2020.  AI is so popular and in demand that it can be no other way.  Now how to use AI is the next big question that needs answering by the vendors and the customers who buy it.  Artificial intelligence needs to be able to help make strategic decisions, enhance the business model and ecosystem, and drive user/customer experiences through to 2025.   Strategic planning in this aspect involves data preparation, integrations, creating new algorithms to run AI, new ways to train personnel how to use AI, and creating new data models.  Personnel involved here are data scientists, developers and business process owners who will have to work together closely. 
  2. Intelligent Apps and Analytics – Apps are beginning to implement AI in how they work.  They cannot exist without AI and machine learning capabilities.  Because of this, it is, in turn, changing how people and systems work together at the workplace.  It doesn’t replace people. It’s a strategic area where analytics uses machine learning to better automate data prep and finding and sharing insights.  People in the company using this are business users, operational workers, and citizen data scientists.   
  3. Intelligent Objects – These are physical things that use AI to operate.  Included here are self-driving cars, robots, and the Internet of Things.  Self-driving vehicles are already in use in agriculture and mining but will take more time spreading to other vehicles, like cars.  By 2022 more streets will become more user-friendly towards them, but more studies need completing. 

Blending of the Digital and Physical Worlds

  1. Digitial Twins –  It defines a representation of real-world entities and/or systems.  This deals with IoT for the most part.  If the twin is built correctly then it can really support improving business decision making processes.  The twin is linked to their counterpart in being able to better understand the state of the system, better responding to changes, improve operations and add more value to the company as a whole.  In the future, they will fuse together with their counterparts and AI type capabilities.  Consequently, people in the company who will use this are city planners, digital marketers, healthcare professionals, and industrial planners. 
  2. Edge Computing – This is where information processing, gathering and delivering content is put closer to the sources of information.  Companies need to begin using edge computing as it supports IoT, creating better connectivity, bandwidth, and functionality.  Cloud helps support this as it doesn’t need a central location.   
  3. Conversation Platforms – This is going to be the one that drives the next change with how people perform and interact with the digital world.  People can talk to computers and the system will be able to act on it.   If the person using the computer is confusing it, it can ask for clarification.  It’s becoming a primary design goal using with hardware, core OS features, platforms, and apps.  Developers need to work on the communication aspect of the platforms, as it’s still very difficult to make them work.  People need to speak very clearly about what they want, and it causes more frustration than anything else right now.   
  4. The Immersive Experience – Virtual, Augmented and Mixed Reality are all here.  For any benefits for business, they need to look at how it can help employees work better.  The design, training and visualization process is key to making this work.  When dealing with Mixed Reality, it’s creating some great technology that might actually be good for the work environment.  Tools already developed and in use includes Head Mounted Displays (HMD) for VR and AR, smartphones and tablet-based AR and environmental sensors. 

Exploiting Connections

  1. Blockchain – This technology is rapidly spreading everywhere, not just for the cryptocurrency.  The blockchain is a disruptive technology as it changes how business is ran, for both startups and enterprises.  The only problem here is that blockchain technology is more promise right now as it’s immature for the next two or three years. 
  2. Event Driven – This includes anything from recording an electronic purchase at your website, to a recording when a plane lands.  Anything action completing dealing with the company is an event.  Because of this IoT, cloud computing, the blockchain, memory data management, and AI are included here.  With these platforms, its ability to find and analyze events more thoroughly grows.  As a result, people involved here include IT leaders, planners, and architects. 
  3. Continuous Adaptive Risk and Trust –  This deals, for the most part, cybersecurity.  There have to be real-time, risk and trust-based decisions and adaptive responses.  Basically, the company needs to embrace opportunities and manage the risk involved with having digital business actions completed.   

Summary 

Strategic information systems planning is very complex.  There are so many different areas needing planning in the next five years in order to keep up with all the new technology.  Most are in its infancy, but it’s growing fast.  Better start planning now! 

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Top 5 Trends From Mobile World Congress 2018

mobile, trends, mobile trends, ai, iot, industrial iot, devices, ai

Source: Forbes

In March this year, there was a mobile trade show that talked about many new trends.  Everything shown there, from AI to 5G.   Here’s a list of them and why they might affect us all… 

  1. 5G – This implements faster connectivity.  Because of improved speeds, the user experience will go up.  In turn, this allows for a better experience between consumers and brands that they might be following.   What’s in reach is 100x better speed than 4G and 10x better than broadband speed.  Because of this IoT, AR, VR and Edge Computing are becoming closer in reach than before.   
  2. Artificial Intelligence – 5G will be able to handle AI for a change.  This is good as AI can be used to plan and manage networks.  Consumer demand predicting is going to become easier.  Easing tariffs will become the norm.   AI and telecommunication are just scratching the surface of what’s to come. 
  3. Augmented Reality – Apparently Google is planning on putting AR in every new smart phone by December 2018.  That will be something to see and will be extremely interesting to see how they will make it work on a phone.  On top of that AR can be used in supply chain management and allow customers to test products almost before buying.  Because of this innovators will be able to better meet demand. 
  4. Industrial IoT – Industrial IoT uses technology differently than if it’s a consumer.  Things needing consideration is moving business data securely from one site to another, sorting it out, and how it’s going to be used. Mostly they were talking about using IoT for tracking vehicles and robotics. 
  5. New Devices Coming to Market – New mobile features will possibly include virtual reality and biometrics.  That will be interesting to see how they can enable those features.   New types of cooling systems and having almost no bezels might just be coming next! 

Summary 

It’s going to be an interesting time, with many new innovations coming to our smartphones.  Because of these changes, it’s going to make everything so much easier to complete without even having to go to PC or Mac it looks.  Just how much customer improvement is there going to be with all these potential implementations?  That’s the big question.    

 

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5 AI Trends to Watch in 2018 (via O’Reilly Media)

ai, trends, machine learning, deep learning, learning

Introduction

From methods to tools to ethics, Ben Lorica looks at what’s in store for artificial intelligence.  Here are five trends to look for in 2018.

Source: O’Reilly Media

 

5 AI Trends for 2018

  1. Progress in machine learning processes – Recently deep learning architectures and algorithms are having vast improvements in the areas of computer vision, speech and text.  Companies expect to use better algorithms.  Because of this, they are implementing training, inference and data processing on newer edge devices.  Machine learning experts will work on new ways to analyze more data through neuro-evolution and deep learning.   With how technical and scientific machine learning is becoming, people are going to start learning more about the process.   
  1. New developments and lower cost – This will allow for better data collection and faster deep learning.  Deep learning uses edge devices and servers.  As a result, there will be new servers, software and optimized systems that will speed up the learning process for the computer at that specific company.  Cost savings will occur using new startups who are starting to market in this area.  Companies need more and more storage for their data.  Alternate sensors and newer methods of gathering and using data are becoming more commonplace.  Higher demand results in lower prices.
  1. Developer tools for AI and deep learning keep on changing – TensorFlow is the most popular.  Caffe, PyTorch, and BigDL are becoming more popular as the demand grows.  New tools will help simplify the architecture and hyperparameter tuning, training, and disbursement.  Progress is expected in simulators that will speed up AI development.  Reinforcement learning libraries will improve also.  AI applications will be able to process multimodal inputs.  Most of all, there will be tools available for those who aren’t data scientists or engineers. 
  1. Use cases for automating – As more companies enter the realm of AI they will discover that automation is best used here or at least semi-automation.  This will include speech and natural language, robotics, and use cases in the health and medical fields.  AI will also be used in more creative fashion, like for music, art, and images.   
  1. Privacy, ethics and responsible AI – Transparency is in high demand now and will be a focus for a long time.  This is along with what is fair and what is explainable.   Responsible AI is key here.  Who wants to hear and see “fake” news all the time?   
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4 Things to Know About the Blockchain System

blockchain, innovation, business, competitive advantage

Source: Harvard Business Review

Introduction

Why is blockchain becoming a trend for businesses?  There’s one area for improvement that needs help in systems today.  It’s contracts, transactions, and records of actions completed.  Paperwork all over the place.  The system in place hasn’t kept up with the rest of the digital age.  Blockchain can help in this arena if companies started to take advantage.   

The blockchain is open source and takes care of virtual currencies. It records transactions between two people buying and selling currency in permanent ways. If blockchain is in the business world, imagine the possibilities.  Storing contracts without worrying about tampering.  All agreements, process, task, and payment go into the records.  People, agencies, machines, and algorithms would be able to contact and communicate with each other with little trouble.   

The problem here is looking after security and breaking down barriers already in place.  The blockchain isn’t considered a disruptive technology because it will create new foundations.  The ramifications are huge.  

The 4 Adaptations for Blockchain

  1. Single Use – Low coordination applications to make better, cheaper, highly focused solutions. 
  2. Localization – High in innovation but don’t need many users to create usefulness. It makes it easier to promote to the rest of the agency. 
  3. Substitution – These build on what’s already in place.  And here there will be high resistance.  It requires coordinating and replacing systems already fully integrated into systems. It could take years to put in place and start using.   
  4. Transforming – These are new items that will be placed into use, creating fast change to economic, social and political systems.  Smart contracts are the best options to start with now.  It automates payments when conditions are met.   

Summary 

Start the blockchain in single-use applications.  There won’t be as much risk taken during changes as they aren’t new and don’t involve much coordination with third parties. Blockchain can help to find problems quickly through tracking processes agencies have in place already.  Another cool thing is that it could possibly cut costs of transactions.  The big thing to consider is this, if blockchain becomes big in business, it will affect your company in some manner.   

 

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5 ways companies are using big data to help their customers (via VentureBeat)

big data, enterprise data, analytics, data analytics, data modeling, data science, data modeling, data model, data, data science, data scientist, data management,

Five ways companies are using big data to treat customers more like individuals — and build better long-term relationships so those customers happily buy more and more

Source: VentureBeat

Review

As we all remember, back in the day you could go to the store and the clerk would know you personally.  They would ask you how you are and how your family is. It was a very personal relationship you would have, therefore creating loyalty between you and the store.  It has been lost for a while when stores started to sell online.  There were no programs to make your shopping experience more personal or enjoyable.  You just went online to search and buy.  Big data helps to build relationships again as it can help companies offer better service to customers if used.   Here are the five ways that big data helps online stores to treat their customers more like people instead of just numbers.

5 Methods to Use Big Data

  1. Prediction – Big data can help analyze past behaviors of customers to build a more personalized experience for them. This in turn creates satisfaction for the person and increases purchases.
  2. Excitement – This is more for wearable technology. FitBit and other companies spew out the data they gather to their clients, which makes the client more interested and excited to see improvements.  This is completed in other industries too, not just the health industry.  There are apps to help track finances too and make people excited to invest more.  Showing the data makes the client happier.  It can show them where they need to work to improve themselves too.  It’s a good tool for the customer to use.
  3. Improvement – Customer service is just as important as effective marketing and product development. Big data can help in all these areas too.  Representatives can answer questions more quickly and effectively when the correct data is in front of them.  This way the customer doesn’t feel like they are being badgered.  The data helps as the customer has so many ways to get a hold of companies now than before.
  4. Identify – Find the difficulties customers are having to improve their experience. It’ll make for happier and more loyal customers.
  5. Reduce – This deals with the health care industry for improving quality of patient care. It helps to cut cost and improve treatments.

Summary

Big data helps companies now to understand their customers better.  This helps agencies give better services and build relationships again, in a more modern way.  Just consider all the possibilities.  I would think about switching over myself if I had a bigger company and could afford it.

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84% Of Enterprises See Big Data Analytics Changing Their Industries’ Competitive Landscapes In The Next Year (via Forbes)

big data, data science, big data analytics, analytics, data modeling, data management, smart data, data mining

87% of enterprises believe Big Data analytics will redefine the competitive landscape of their industries within the next three years. 89% believe that companies that do not adopt a Big Data analytics strategy in the next year risk losing market share and momentum. These and other key findings are from an […]

Source: Forbes

I just thought that I would share this article.  It has some great statistics on why Big Data is now considered essential for any type of competitive growth.  For example, only 13% use Big Data analytics in predictive modeling, while only 16% are using the information that they find to improve processes.  If you were to use Big Data analytics, image what kind of growth your business could have…

I love studies as they always show the numbers to help strengthen their arguments.  Just wanted to share this with you all.

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Data Modeling Trends in 2018 – DATAVERSITY (via DATAVERSITY)

data modeling, data science, data scientist, data, data security, ai, machine learning, deep learning, big data, Big Data, enterprise data, data management, internet of things, iot, smart data

The Database Management and Data Modeling landscapes have evolved much in the past few years, from the traditional relational model to now include non-relational models as well.

Source: DATAVERSITY

Review of Article

Advantages of Data Modeling

  1. Provides clear framework for development projects
  2. Enables high performance
  3. Corrupt datasets are found quickly and cleaned before using
  4. Offers tested models for building software
  5. Outlines scope and risks during development
  6. Includes detailed documentation which helps with future maintenance

New Trends

  • Wide variety of machine facts to include Internet of Things (IoT)
  • Scale and speed of data increasing along by machine learning
  • Demand of aggregated data is increasing
  • Public, private on-site Cloud storage
  • Huge amounts of data collected into what is Data Lakes (unchanged data) for data scientists to analyze later
  • Automated data modeling (algorithms)
  • Predictive modeling with advanced machine learning
  • Semantic data models

SQL Database Trends 2018

  • Adoption rates will differ as companies due to security concerns
  • Cloud adoption
  • AI capabilities are increasing
  • SQL Servers for Linux
  • There are new schedules for software updates (handled by the vendors themselves, not Microsoft like before)
  • Use of Data Vaults

Summary

It sounds pretty exciting doesn’t it?  So many changes to look forward to trying out for your business.